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ACMSE
2006
ACM
13 years 9 months ago
Hybrid intelligent systems for network security
Society has grown to rely on Internet services, and the number of Internet users increases every day. As more and more users become connected to the network, the window of opportu...
J. Lane Thames, Randal Abler, Ashraf Saad
BMCBI
2010
170views more  BMCBI 2010»
13 years 7 months ago
Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks
Background: The aim of this study was to provide a framework for the analysis of visceral obesity and its determinants in women, where complex inter-relationships are observed amo...
Alex Aussem, André Tchernof, Sergio Rodrigu...
ICML
2008
IEEE
14 years 8 months ago
Laplace maximum margin Markov networks
We propose Laplace max-margin Markov networks (LapM3 N), and a general class of Bayesian M3 N (BM3 N) of which the LapM3 N is a special case with sparse structural bias, for robus...
Jun Zhu, Eric P. Xing, Bo Zhang
JAIR
2010
181views more  JAIR 2010»
13 years 2 months ago
Intrusion Detection using Continuous Time Bayesian Networks
Intrusion detection systems (IDSs) fall into two high-level categories: network-based systems (NIDS) that monitor network behaviors, and host-based systems (HIDS) that monitor sys...
Jing Xu, Christian R. Shelton
NECO
2002
104views more  NECO 2002»
13 years 7 months ago
An Unsupervised Ensemble Learning Method for Nonlinear Dynamic State-Space Models
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
Harri Valpola, Juha Karhunen